RNA Sequencing Facilitates Quantitative Analysis of Control and GLUT1-HK2-PFKFB3 Overexpressed Transcriptomics in Mouse Skeletal Muscle
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ABSTRACT:
PROVIDER: PRJNA660662 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR12563620_1.fastq.gz | Fastqsanger.gz | |||
| SRR12563620_2.fastq.gz | Fastqsanger.gz | |||
| SRR12563621_1.fastq.gz | Fastqsanger.gz | |||
| SRR12563621_2.fastq.gz | Fastqsanger.gz | |||
| SRR12563622_1.fastq.gz | Fastqsanger.gz |
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Project description:Purpose: RNA-Seq uses next-generation sequencing to analyze expression across the transcriptome, enabling to detect known or novel features and quantify RNA. The goal of this study is to compare transcriptome profiles between control and GLUT1-HK2-PFKFB3 overexpressed mouse skeletal muscle. Methods: Total RNA was isolated from the gastrocnemius muscle of chow diet-fed M;G and control mice at the age of 3-month-old using RNAiso Plus (Takara Bio). Three independent pooled samples per group were analyzed. Sequencing libraries were generated using NEBNext® UltraTM RNA Library Prep Kit for Illumina® (NEB, USA) following manufacturer’s recommendations and index codes were added to attribute sequences to each sample. The clustering of the index-coded samples was performed on a cBot Cluster Generation System using TruSeq PE Cluster Kit v3-cBot-HS (Illumia) according to the manufacturer’s instructions. After cluster generation, the library preparations were sequenced on an Illumina Hiseq platform and 125 bp/150 bp paired-end reads were generated. Index of the reference genome was built using Hisat2 v2.0.5 and paired-end clean reads were aligned to the reference genome using Hisat2 v2.0.5. Fragments Per Kb of exon per Million mapped reads (FPKM) were calculated using featureCounts v1.5.0-p3. Results: We mapped about 6 million sequence reads per sample to the mouse genome and identified 54533 transcripts in the gastrocnemius muscle of control and GLUT1-HK2-PFKFB3-overexpressed mice. RNA-seq data confirmed stable expression of 10 known housekeeping genes, and 7 of these were validated with qRT–PCR. A total 664 transtripts were differentially expressed in wildtype and GLUT1-HK2-PFKFB3 overexpressed skeletal muscle with a cutoff of 2.0-fold and p < 0.05 from RNA sequencing analysis. Altered expression of 15 genes was confirmed with qRT–PCR, demonstrating the high degree of sensitivity of the RNA-seq method.
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Project description:Purpose: In this study, we compared transcriptome profiling (RNA-seq) between normal mouse embryonic stem cell (E14) and Hexokinase2 (Hk2)/ Pyruvate Kinase M2 (Pkm2) overexpressed E14 cell. Result: Using an optimized data analysis workflow, we mapped over 4 billion sequence reads per sample to the mouse genome (build mm9) and identified 28698 transcripts in 5 samples. Conclusion: Our study represents the first detailed analysis of Hk2/ Pkm2 overexpressed E14 cell transcriptomes, generated by RNA-seq technology We compared transcriptome profiling (RNA-Seq) between normal mouse embryonic stem cell (E14) and E14 cells over-expressing Hexokinase2 (Hk2)/Pyruvate Kinase M2 (Pkm2)
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Project description:Published molecular profiling studies in patients with lymphoma suggested the influence of hypoxia inducible factor-1 alpha (HIF1α) targets in prognosis of DLBCL. Yet, the role of hypoxia in hematological malignancies remains unclear. We observed that activation of HIF1α resulted in global translation repression during hypoxic stress in DLBCL. Protein translation efficiency as measured using 35S-labeled methionine incorporation revealed a ≥50% reduction in translation upon activation of HIF1α. Importantly, translation was not completely inhibited and expression of clinically correlated hypoxia targets such as GLUT1, HK2, and CYT-C was found to be refractory to translational repression under hypoxia in DLBCL cells. Notably, hypoxic induction of these genes was not observed in normal primary B-cells. Translational repression was coupled with a decrease in mitochondrial function. Screening of primary DLBCL patient samples revealed that expression of HK2, which encodes for the enzyme hexokinase 2, was significantly correlated with DLBCL phenotype. Genetic knockdown studies demonstrated that HK2 is required for promoting growth of DLBCL under hypoxic stress. Altogether, our findings provide strong support for the direct contribution of HK2 in B-cell lymphoma development and suggest that HK2 is a key metabolic driver of the DLBCL phenotype.ne incorporation revealed a ≥50% reduction in translation upon activation of HIF1α. Importantly, translation was not completely blunted and expression of clinically correlated hypoxia targets such as GLUT1, HK2, and CYT-C was found to be refractory to translational repression under hypoxia in DLBCL cells. Notably, hypoxic induction of these genes was not observed in normal primary B-cells. Translational repression was coupled with decrease in mitochondrial function. Screening of DLBCL patient samples identified that expression of HK2, which encodes for the enzyme hexokinase 2, was significantly correlated with DLBCL phenotype. Genetic knockdown studies show that HK2 is required for promoting growth of DLBCL under hypoxic stress. Altogether, our findings provide more definitive proof of direct contribution of HK2 in development of B-cell lymphoma and suggest that HK2 is a key metabolic driver of DLBCL phenotype.
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Project description:We hypothesized that PFKFB3 inhibits fructose metabolism in pulmonary microvascular endothelial cells (PMVECs) and found that PFKFB3 knockout cells survive better than wild type cells in fructose-rich media, more so under hypoxia. Our findings indicate that PFKFB3 is a molecular switch that controls glucose versus fructose utilization in glycolysis and help to better understand lung endothelial cell metabolism during respiratory failure.
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